Title :
Approximation of the Two-Part MDL Code
Author :
Adriaans, Pieter ; Vitányi, Paul M B
Author_Institution :
Comput. Sci. Dept., Univ. of Amsterdam, Amsterdam
Abstract :
Approximation of the optimal two-part minimum description length (MDL) code for given data, through successive monotonically length-decreasing two-part MDL codes, has the following properties: (i) computation of each step may take arbitrarily long; (ii) we may not know when we reach the optimum, or whether we will reach the optimum at all; (iii) the sequence of models generated may not monotonically improve the goodness of fit; but (iv) the model associated with the optimum has (almost) the best goodness of fit. To express the practically interesting goodness of fit of individual models for individual data sets we have to rely on Kolmogorov complexity.
Keywords :
codes; computational complexity; Kolmogorov complexity; data set; two-part MDL code; two-part minimum description length code; Computational modeling; Computer science; Entropy; Government; Information theory; Machine learning; Pattern analysis; Probability; Shape; Sorting; Approximation; Kolmogorov complexity; MDL code; minimum description length (MDL); model fitness; model selection; structure functions;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2008.2008152